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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

Is sea level rise accelerating?

What the science says...

Looking at global data (rather than tide gauge records just from the U.S.) show that sea level rise has been increasing since 1880. The recent rate of sea level rise is greater than its average value since 1930. As for future sea level rise, these predictions are based on physics, not statistics.

Climate Myth...

Sea level rise is decelerating
"A former research director with the Army Corps of Engineers and a former civil-engineering professor at the University of Florida decided to put the sea-rise claims to the test. They gathered U.S. tide-gauge readings from 57 stations where water levels had been continuously recorded for as long as 156 years. The result did suggest the sea level was increasing in the western Pacific, but this was offset by a drop in the level near the Alaskan coast. “Our analyses do not indicate acceleration in sea level in U.S. tide gauge records during the 20th century,” the study’s authors concluded. “Instead, for each time period we consider, the records show small decelerations that are consistent with a number of earlier studies of worldwide-gauge records." (Washington Times)

A paper by Houston & Dean studies 57 tide gauge records from the U.S. (including Hawaii and oceanic territories) and concludes that sea level rise has not accelerated. In fact the authors seem to go out of their way to state that the average result shows deceleration at every opportunity. But there are some big questions about their analysis. Why do they use tide gauge records from just U.S. stations? Why not a global sample? Why use individual tide gauge records when we have perfectly good combinations, from much larger samples, which give a global picture of sea level change and show vastly less noise? Why do they restrict their analysis to either the time span of the individual tide gauge records, or to the period from 1930 to 2009? Why do they repeatedly drone on about “deceleration” when the average of the acceleration rates they measure, even for their extremely limited and restricted sample, isn’t statistically significant?

But the biggest question of all is: what’s the big deal?

Here’s some sea level data, in fact two data sets. One is a global combination of tide gauge records by Domingues et al. (2008, Nature, 453, 1090-1094, doi:10.1038/nature07080). Using around 500 tide gauge records globally, it’s the latest version of the “Church & White” dataset. The other is satellite data:

I averaged the two data sources during their period of overlap, and computed a smoothed version:

This is a global data set, and it’s a worldwide average so its shows vastly less noise than individual tide gauge records. We could even use it to look for acceleration or deceleration in sea level rise. But one thing we should not do is restrict consideration to the quadratic term of a quadratic polynomial fit from 1930 onward. That would be pretty ignorant — maybe even misleading.

As so often happens, one thing to be cautious of is that the noise shows autocorrelation. As Houston & Dean point out, the Church & White data since 1930 are approximately linear, so to get a conservative estimate of the autocorrelation I used the residuals from a linear fit to just the post-1930 data and fit an ARMA(1,1) model.

If we compute the linear trend rate for all possible starting years from 1880 to 1990, up to the present, we get this:

According to this, the recent rate of sea level rise is greater than its average value since 1930. Significantly so (in the statistical sense), even using a conservative estimate of autocorrelation. But the increase itself hasn’t been steady, so the sea level curve hasn’t followed a parabola, most of the increase has been since about 1980. How could Houston & Dean have missed this?

Here’s how: first, they determined the presence or absence of acceleration or deceleration based only on the quadratic term of a quadratic fit. That utterly misses the point. Changes in the rate of sea level rise don’t have to follow a parabola, since 1930 or any time point you care to name. In fact, by all observations and predictions, they have not done so and will not do so.

Second, by using individual tide gauge records, the noise level is so high that you can’t really hope to find acceleration or deceleration of any kind, with any consistency. Not using quadratic fits, and certainly the non-parabolic trend which is present can’t be found in such noisy data sets.

Even so, we can also fit a quadratic (as Houston & Dean did), and estimate the acceleration (which is twice the quadratic coefficient):

Well well … it looks like starting at 1930 is the way to get the minimum “acceleration” by this analysis method. Could that be why Houston & Dean chose 1930 as their starting point?

If we restrict to only the data since 1930, as Houston & Dean did, and fit a quadratic trend, we get this:

Can you tell, just by looking, whether it curves upward or downward? Clearly, the parabolic fit doesn’t show much acceleration or deceleration, if any. We can get a better picture by first subtracting a linear fit, then fitting a parabola to the residuals?

That answers the question: the quadratic fit shows acceleration in the Church & White data. But, when autocorrelation is taken into account, the “acceleration” is not statistically signficant.

But — just because the data don’t follow a parabola, doesn’t mean that sea level hasn’t accelerated. Let’s take those residuals from a linear model, and fit a cubic polynomial instead:

Well well … there seems to be change after all, with both acceleration and deceleration but most recently, acceleration. And by the way, this fit is significant.

And now to the really important part, which is not the math but the physics. Whether sea level showed 20th-century acceleration or not, it’s the century coming up which is of concern. And during this century, we expect acceleration of sea level rise because of physics. Not only will there likely be nonlinear response to thermal expansion of the oceans, when the ice sheets become major contributors to sea level rise, they will dominate the equation. Their impact could be tremendous, it could be sudden, and it could be horrible.

The relatively modest acceleration in sea level so far is not a cause for great concern, but neither is it cause for comfort. The fact is that statistics simply doesn’t enable us to foresee the future beyond a very brief window of time. Even given the observed acceleration, the forecasts we should attend to are not from statistics but from physics.

Comments

Here’s some sea level data
, in fact two data sets. One is a global combination of tide gauge records by Domingues et al. (2008, Nature, 453, 1090-1094, doi:10.1038/nature07080). Using around 500 tide gauge records globally, it’s the latest version of the “Church & White” dataset. The other is satellite data:
...
If we compute the linear trend rate for all possible starting years from 1880 to 1990, up to the present, we get this:

The above chart, as I understand it, uses data from 1880 all the way up to the present, but the plot only covers 1880 to 1990. The last 20 years have been left off. If the plot were to continue right up to the present the time line would become very erratic as the sample size approaches unity and becomes meaningless. Essentially large sample sizes early in the time line are compared with numerically smaller samples of more recent data. In everyday language, it's comparing apples and oranges. The cutoff at 1990 would indicate that a 20 sample size is appropriate.

So why not look at 20 year slices of trend rate back through time and see how they compare? And lets use all of the data all the way to the present.

So if we compute the linear trend rate for all possible 20 year periods starting with 1807 - 1827 then 1808 - 1828 and so on up to the present, we get this:

An entirely different picture is painted when each data point represents an equal sample size. The early years are erratic because of a small number of tide gage records.

The above link "some sea level data" didn't work for me, I used data from the PSMSL that dates from 1807 from over 1200 tide gages. The data is grouped and averaged by coastlines and the median value take for each year in the time line.

I assume that the Church & White/satellite data would plot out in a similar fashion as above.

Steve Case @1, the PMSL site warns that its data has not been adjusted for Glacial Isostatic Rebound, a caution you should have taken to heart. As it happens, the data set not only has very few stations predating about 1930, but they are not geographically representative. Rather, they are taken almost entirely from the East Coast of the United States, and northern Europe. The East Coast of the US and the southern shore of the Baltic are both experiencing strong local rises in sea level due to the Glacial Isostatic Adjustment, significantly biasing your sample.

Indeed, even as late as 1980, there are just 5 stations in South America, and 2 in Africa (both in Morrocco). So at no time interval of your data set is a simple mean geographically representative, and through out the time period trends are as much a function of increases in station numbers in various areas as they are a feature of the actual record.

If you where to apply your analysis to the Domingues et al data set, and come up with a similar result, you may then have a valid criticism. As it stands you do not even raise an interesting question.

Piling 130 years worth of data into a data point from 1880 and comparing it to a data point from 1990 made up of only 20 years worth of data and then omitting the plot for the last 20 points in the time series, does not make any sense.

The graph from such a scheme leads one to believe that sea level rise during earlier periods showed no variation from year to year. That is not the case.

At the moment I have no way of downloading the data from the link above. Otherwise I would have used that data to create the plot.

I have run the Peltier GIA adjustments on the GLOSS sites from the PSMSL and all it does is increase the slope by about 0.5 mm/yr.

Did you read the original post? This is a repost of one written by tamino; it is used here as a rebuttal of work by Houston and Dean. Tamino is simply (and quite effectively) making the point that the authors' conclusions - that sea level rise is linear - are unjustified.

The key point is in his last paragraph:

the forecasts we should attend to are not from statistics but from physics.

You have fallen into the usual trap of looking first for correlation, and then assuming there must be some mystical if undefined causation behind it.

The better approach is to anticipate a cause, through an understanding of the mechanics and physics of the system, and to make a hypothesis, and then to either confirm or refute that hypothesis through correlation (or lack of correlation) in observations.

The distinction between the two methods is dramatic, necessary, and where so many denial efforts fail before they even get out of the gate, because the former methodology is founded on ignorance and superstition rather than education and logic like the latter.

Steve Case @3, even if the method were appropriate, the fact that you use unrepresentative data both in time and space means your analysis is not indicative of global twenty year trends in sea level rise. Go to the PSMSL page on relative trends, and use the slider on the bottom and you will see what I mean.

Take on example. In 1930, East Asia is represented by just six gauges, all in Japan. By 1970 it is represented 88, mostly in Japan and South Korea. At no time is a simple mean representative of East Asia geographically, and the weight assigned to East Asia (or more particularly Japan) in a global average changes continuously over the period 1930 to 1970.

So, while I am not disputing your use of successive 20 year trends as a means of establishing the change in global trends, I am disputing your use of a data set which is never geographically representative, and which changes the representation of various regions over time in order to determine those trends.

As ever, DB provides the best information, and you would do well to look carefully at the second figure (fig 8) in his inline comment. Applying 16 year trends on a consistent and representative data set shows a very distinct pattern to that shown from your simple mean of the PSMSL data set.

Tom, Thank you for not disputing the use of twenty year trends as a means of establishing the change in global trends. What about disputing the use of ever shorter trends as a means of establishing that change? That's what Tamino has done when he computed the linear trend rate for all possible starting years from 1880 to 1990, up to the present. The resulting graphic effectively ignores any changes in global trends early in the century and magnifies more recent changes. Had the graphic included points derived in that manner since 1990 the magnification and distortion would been gross and apparent.

The PSMSL data is arranged by coast line and geographic coordinates which allows the user to perform more than a simple mean. There are 167 coastlines reported. Coast lines have anywhere from one to 77 reporting stations. For each coast line for each year I took the average. The geographic coordinates allow an estimate of each coastline size and application of an appropriate weight for each. For each year I took the median of all 167 coast line averages. That's not to use your assessment, a simple average.

I also applied the Peltier GIA adjustment to the GLOSS stations. I found out that it increases the slope by about 0.5 mm/yr but does not otherwise change the shape of the timeline.

I would like to analyze the Domingues et al data of those around 500 tide gages. But as is the case in many data files, special programs are needed to unlock them. And so far they are unavailable to me. By the way, the PSMSL data is over 1200 tide gages.

I intend to ignore any further critiques you have about the PSMSL data as it's not the issue.

And the issue is method. Using unequal sample sizes as Tamino did that magnify recent changes and ignore earlier ones results in a gross distortion.

"What about disputing the use of ever shorter trends as a means of establishing that change? That's what Tamino has done when he computed the linear trend rate for all possible starting years from 1880 to 1990, up to the present."

That is not what Tamino has done. Tamino is testing a particular claim, ie, that the rate of change in global sea level has decelerated over the course of the twentieth century (or at least since 1930). Plotting the trend to end point for each year in succession will, as you suggest, exagerate the magnitude of more recent trends relative to older trends. It will show greater variability in the more recent trend. But it will not determine whether the recent trends are larger than the long term trend, or smaller. If in fact the rate of change of sea level was decelerating as is claimed by Houston and Dean, then the most recent trends would be smaller than the long term trends, and plotting a graph such as Tamino's third figure will show a steady line falling away towards zero at the end.

So if that is your point, you have no point. You would do well to reread Tamino's post and pay attention to the other more important statistical techniques Tamino applies to determine the evolution of the rate of change of sea level over the 20th century.

2) If you want to introduce your chart as evidence, you need to defend its construction. If you don't want to defend its construction, you ought to withdraw it. As it stands, however, it appears you want to make use of a graph in which artifacts of the data will introduce a very large amount of noise.

If you are simply trying to make a logical point about Tamino's analysis, I do not understand why you insist on the accuracy of your graph when you could make the same points using the graph provided by DB inline @1.

You, however, insist on sticking with your graph, which makes me suspect some feature of that graph is important to the point you are trying to make. But to the extent that your graph differs from that supplied by DB, there is very good reason to think that the difference is due to noise introduced by your methods.

Add all the higher orders you like, but be sure to check if they are statistically significant add-ons. That's exactly what was done by tamino; apparently you still have not read that post in full. That would be far more conducive to a rational discussion than any further announcements of your intent to ignore relevant critiques.

In the quest for significance, you would do well to consider the work of Kemp et al 2011:

Sea level was stable from at least BC 100 until AD 950. Sea level then increased for 400 y at a rate of 0.6 mm/y, followed by a further period of stable, or slightly falling, sea level that persisted until the late 19th century. Since then, sea level has risen at an average rate of 2.1 mm/y, representing the steepest century-scale increase of the past two millennia.

I'd suggest, as others threads already have, that long-term pattern is described accurately as 'accelerating.' And that does not even reflect the 3.2 mm/yr from the graph you posted above.

Steve Case @9, congratulations. You have taken a curve bracketed by the Mount Pinatubo eruption at one end, a cluster of strong La Nina's a the other, and with a number of strong El Nino's in the middle. Unsurprisingly the rate of sea level rise from the Pinatubo low to the El Nino highs is slightly greater than the rate from the El Nino highs to the La Nina lows.

If you take a longer data set, as Tamino did you find that sea level rise is accelerating, just as Tamino shows.

Now you may insist that we should pay more attention to the shorter trend. However, the shorter trend shows a strong dependence between mean sea temperatures and sea level heights. That is not a comforting thought for the future.

Tamino did not address the totality of the data, he left off the last 20 years. He used 1880 to present for his calculations, but only graphed them up to 1990. Had he actually addressed the totality of the data in his graph it would have had a time line up to the present and the distortions would have been plainly obvious.

Steve Case @13, on the contrary, Tamino carries his data through to 2009, which considering that the data comes from a 2008 paper clearly shows a commitment to using all the available data. The first graph only goes to 1990 because it graphs from the indicated year to the present (2009). 1990 represents the most recent year on that basis for which the data supports a trend of at least 20 years. Short term trends, in climate science, are almost all noise and so of no interest.

In an earlier post I said I was having trouble downloading the data from the link provided by "Here’s some sea level data" in the "What the Science Says" lead at the top of this page. If you follow that link you will come to a page with a table at the bottom. The links in that table aren't accessable to the average user. My son is an IT professional and he told me it was very difficult and stopped before he got any useful information.

So I ran the obvious comparison against the analysis I had done of the PSMSL data and got the following result:
And indeed, the Church and White data obviously shows an increase in the rate in sea level rise over the last century. I don't need an analysis from Tamino to tell me that.

The difference in the two timelines has to come from the decisions Church and White made as to what data to include, and what data to omit. All of the data used is available at the PSMSL site, it's just a matter of figuring out what Church and White omitted. ( -Snip- )

We are told in the paper that "Careful selection and editing criteria, as given by Church et al. (2004) were used." And the 2004 opus, a pay per view link, provides an abstract that doesn't touch on editing criteria.

So as far as I'm concerned, it's essentially a "Black Box" that decided what data to omit.

I will probably do some sort of sampling as the downloaded data tells us what years were included and I will have to determine what the omitted data is and what that does to the slope. For example, at random I chose the first station I found where the available data was truncated:

A random sample of 30 would give me a good idea, but as I say, I know what I'm going to find, it's a question of what was the criteria for data selection? And why does that criteria tend to skew the results one way?

Response:

[DB] Speculations into motive snipped. Either formulate a comment that doesn't cast aspersions into other's integrity or don't post here.

Future comments containing such speculations and aspersion will be deleted outright.

It seems to me that this question is ambiguous. Without a uniform starting line, either could be shown to be true.

While no is arguing that sea level has not accelerated since the end of the little ice age (where sea levels actually dropped), the tidal gauge data since 1880 has shown an overall acceleration. The cubic fit to the residual linear curve shows that acceleration and deceleration of sea level rise followed the temperature during the 20th century. Clearly the sea level has accelerating since 1980. However, in the even shorter term, sea level rise as decelerated since 2000.

Response:

[DB] In your ongoing desire to prosecute your agenda, you continue to cherry-pick by focusing on a small, statistically insignificant, portion of the data available.

The methodology we are told involves "Careful selection and editing criteria, as given by Church et al. (2004) And as I pointed out in my post, Church et al (2004) is a pay per view opus with no reference to criteria in the abstract.

You extracted the raw PSMSL data in less than a minute? I'm impressed.

Yes, the Church & White data, once you find the nearly hidden link downloads into Excel in about a minute.

I used the raw PSMSL data that you get from the PSMSL website

http://www.psmsl.org/data/obtaining/

Here’s the link to data for Station #1, Brest France:

http://www.psmsl.org/data/obtaining/rlr.annual.data/1.rlrdata

It's not a small sample, there are over 1200 tide gages listed in the PSMSL I used them all. Church and White only used about 500 and then selected only portions of the data according to their criteria in Church et al. (2004) that I don't have access to without paying money.

What this graphic
shows is the difference between my straight forward analysis by grouping raw data by coastline as opposed to using an editing criteria on the raw data first.

Church and White then took that edited data and further applied it to a gridded map using the latitude and longitude coordinates given in the PSMSL. But the raw data was edited first.

I think it's the editing criteria that produces the difference in the time lines above. I doubt that the application of gridded data has much to do with it.

I agree that some of the data is out of whack, if you look up Cyprus in the PSMSL for example, you will find that it's way off. But I have no idea why Church and White edited station #1234:

Maybe some one who has plunked down the cash for Church et al. (2004) can summarize what the editing criteria is.

Response:

[DB] If you were perchance to take the attitude of genuinely trying to research this instead of ascribing untowards motives to those publishing research and if you perchance were to genuinely ask for help when stuck instead of just airing complaints about paywalls, then perhaps someone might help you.

Like pointing out that Church et al 2004 was available for free opus download from the publisher, Journal of Climate:

You complained that this posting
of the complete satellite record included the effects of volcanoes, El Niño and La Niña so I took them out to see what it would look like:
I'd say that it didn't have any effect.

I'd say that according to the satellite record, the rate of sea level rise is not accelerating.

I'd say that you're taking far, far too short a time period to draw such a conclusion, and completely missed the point about Pinatubo and the ENSO events. There is no way to "subtract" them as you have, and even then... you left in the La Nina events that Tom was referring to, i.e. those from 2007 to the present.

Because Pinatubo occurred at the beginning of your series it artificially depressed temperatures. Once that effect tapered off, the system rebounded, gaining the energy it had temporarily shunned. The end result is a more rapid increase in temperature in that time span (i.e. the beginning of your selected period), and in turn a more rapid sea level rise.

The end of your series, conversely, includes an unusual series of La Nina events from 2007 to the present. This very brief period of apparent cooling will naturally retard sea level rise in the short term at the end of your curve.

So you have selected a period where there is an artificially exaggerated increase at the beginning (a steep slope) and an artificial leveling at the end (a shallow slope).

It is no surprise to anyone that you are able to "fit" the curve that you have, but that fit is meaningless.

La Niña and El Niño occur all the time. Here's a link to a NOAA page
that lays it all out since 1950

Here's a graphic and trend of that data since 1993
The trend is down over that period of time. Pretty much as you say. Volcanos come and go. Sea level is what it is over that same period of time. The satellite record date happened to start in 1993. That's the way it is. That you want to complain about it is isn't anything I can do much about.

Response:

[DB] "The satellite record date happened to start in 1993. That's the way it is. That you want to complain about it is isn't anything I can do much about."

You continue to cherry-pick by only using a small portion of the data available. Satellites only represent a portion of the data available to us. The consiliance of these datasets paints a different picture:

Your laser-focus on the most recent period of data while ignoring that which came before it blinds you to the larger trend while magnifying the natural variability inherent in the system.

In a nutshell, you can't see the forest because you have a tree in the way. That's the way it is.

Steve - we've got a few posts on sea level rise coming up. I agree with you sea level rise in the 'noughties' has tapered off somewhat. But we, no doubt, disagree on what that really means.

I'm awaiting on news on publication of a couple of papers on aerosols and subsequent global dimming over the last decade. Both papers shed light on why we have seen a 'slow-down' in global warming in the last decade.

That you want to complain about it is isn't anything I can do much about.

No, I'm not "complaining," I am simply pointing out that the period which you selected, whatever your reasons, is hampered by a large number of factors which make it useless to use for an argument one way or the other.

You cannot draw any conclusions about sea level rise acceleration using the period and data you have selected.

That it shows what you want it to show, and so you are willing to easily overlook these issues, apparently isn't anything I can do much about.

Other readers, however, can easily recognize what is being discussed and decide for themselves what the science says, and what can easily be done to promote false conclusions by creating scientific looking but invalid presentations, graphs and whatnot.

Really, because Topex/Poseidon didn't cover the range they tossed the data? I don't think that makes sense, but I suppose there's a reason for that.

In the text they go from 1658 records down to 945 records but don't give us any numbers as to how many were eliminated for the five reasons tabulated above. Residual Trends <10 mm/yr is reasonably objective. The other four listed are somewhat subjective without any guidelines as to what constitutes unsuitable locations, too much noise, too much fragmentation, or how much disagreement with other records is allowed or how near by they must be. After combining the 945 records there was another group of records eliminated for having no useful data. What was not useful? Perhaps in the data file that defies downloading for me, that is spelled out and each and every deletion is annotated as to how the criteria were met. As it stands right now and as far as I’m concerned, there is room for some subjectivity in perhaps several hundred deletions of data.

A simple analysis of the data yields one thing, and the process along with the above editing criteria yields the opposite.
Now even though there's a difference in sign, if the two time lines were close no one would care, but as you can see,
they're not.

From time to time I have e-mailed some of the principle names in Climate Science with a specific question but mostly I don't want to waste their time and I don't expect a dialog with them although it did happen once. Furthermore they don't show up on blogs, if they do it isn't under their own name. I most certainly am not going to e-mail John Church to criticize his paper. I don't consider Tamino a principle or objective.

Response:

[DB] "I don't consider Tamino a principle or objective."

Well then, let me ask you this:

How many legs does a dog have if you call the tail a leg?

Four; calling a tail a leg doesn't make it a leg. (Abraham Lincoln)

Discounting Tamino's analysis because you don't like it or don't consider him objective doesn't detract from the fact the Tamino is a professional time-series analyst whose work in climate science not only stands the test of time but is widely considered a de facto standard in climate science.

Yes, Tamino can be irrascible. Mostly that stems from those who refuse to learn, have a large vein of Dunning-Kruger running through them and those slander working climate scientists. We are similar in that regard. But again, that does not detract from his work.

If you have issues with the work that forms this post, take it up with him. If you have questions regarding the work of Church & White, take it up with them (I have yet to find a climate scientist unwilling to help those with genuine questions about their work).

1) Records where not eliminated if they where longer than 2 years in length (as you, perhaps mistakenly, indicate), but because they were shorter than two years after 1 or 2 month gaps in the record had been infilled. The obvious reason is that a 2 year record tells you almost nothing about long term trends.

2) The 1063 records eliminated on the basis of redundancy where eliminated because they where duplicate records.

3) The 95 records eliminated because they where outside the Topex coverage where eliminated because the study was an explicit comparison of the tidal gauge and Topex data. Such a comparison can only be sensibly be made over the area in which Topex gathers data.

4) Likewise the data eliminated because it was more than 250 km from one of the Topex grid points was eliminated because it could not be directly compared to Topex data.

5) Contrary to your claim, and as you yourself calculated, there were 713 records eliminated because disagreement among closely located tide gauges, physical location, very noisy data, or very high trends provided reason to believe the tide gauge was measuring unusual local circumstances (subsidences, siltation, etc) rather than global changes in sea level. That the number eliminated for each of these reasons is not recorded separately is irrelevant.

6) No records where eliminated by combination. Combination means that "Where there were multiple tide gauges for a single grid point, the change in height at each time step were averaged to produce a single time series." If we are to call that "elimination" then when you took averages of data for each coast line, you 'eliminated' over 1033 records when you took averages by coastline (see your @7)

I need to make these preliminary points to clean up your tendentious and inaccurate description of Church and White's method.

"I intend to ignore any further critiques you have about the PSMSL data as it's not the issue."

I responded @8:

" If you want to introduce your chart as evidence, you need to defend its construction. If you don't want to defend its construction, you ought to withdraw it. As it stands, however, it appears you want to make use of a graph in which artifacts of the data will introduce a very large amount of noise."

Well, it turns out that you do want to introduce your chart as evidence, and have done so @15, @18, and @25. However, you show no inclination to defend it against previously mounted criticisms which show the chart to be dominated by noise. Rather, you falsely call it a "straight forward analysis", using a label rather than a defense of your methods to suggest the chart is actually worth anything.

So let's compare Church and White's analysis with your supposedly straightforward analysis:

Grouping:
Church and White: Data grouped by cell with a maximum 250 km radius from the center point of the cell;
Case: Data grouped by arbitrary 'coastlines' with no consistent principle in determining coastlines applied across all data. Specifically, all nations are given a separate coast line no matter how small. Some coast lines ared divided by necessity of contiguous status. Thus Canada has two coast lines, one for the west coast, and one for the east and north coast. In contrast the US has separate coastlines for the contiguous Gulf and East coast coastlines. Australia has just one coastline for the entire continent plus offshore islands, while the US has separate coastlines for not just the Gulf and east coast, but also for the west coast, for Alaska, for Hawaii, and for the Aleutians.

Correction poor geographical sampling:
Church and White:

"Our approach relies on resolving large-scale ocean variability by using as many tide gauges as possible to estimate the global distribution of sea level for each month/year between 1950 and 2000. We use sea surface height anomaly satellite altimeter data to estimate the global covariance structure as expressed in empirical orthogonal functions (EOFs). We then estimate the amplitude of these EOFs by using the relatively sparse but longer tide gauge records. The estimated (reconstructed) global distribution of sea level for each month is obtained as the sum of these EOFs.

Correction for large scale changes in air pressure:
Church and White: Reverse Barometric applied;
Case: None.

Personally, I do not think geopolitics to be the most straightforward way to group data in determining mean sea level. That is, however, the basis of your method. Beyond that, what distinguishes your method is the assumption that the silting of estuaries, land slumping or subsidence etc are of no relevance in measuring sea levels. So while your method can be called simplistic, it is false to call it straight forward.

2) The large gap between your graph and that by Church and White is almost entirely a consequence of a >50 mm fall in sea level in 1883 in your graph. You may want us to believe that was a genuine fall in sea level, rather than an artifact of your shoddy methods, but we are not that easily conned. When that obvious artifact of noise in your chart exists, however, it is disingenuous to call attention to the gap between your chart and Church and White's as if that gap some how called Church and White's analysis into question.

Steve Case @19, below is the HadSST2 measure of global sea surface temperature for the period of January, 1990 to December, 2011. As you can see, the convex shape of the 60 month mean is not a function simply of one or two years at the start, or just 1998 (and is clearly not a function of 2011, which is not included.

Your attempt to obviate my criticism @11 clearly ignores the duration of Pinatubo's cooling effect, and the El Nino's of 2003, 2005, and 2007, and the La Nina's of 2008 and 2009.

The fact that it is so easy to pick out a physical cause of the slightly decelerating sea level rise of over the period 1992-2011, and that that cause is sea surface temperatures should not be giving you confidence for the future. More importantly for the present discussion, it should reinforce in you the need to only consider the trends which are statistically significant.

The GIA adjustment changes the overall slope of the time line, and gives it a boost of a bit over 0.5 mm/yr. It doesn't change the shape of the curve. That is to say it has nothing to do with acceleration rates of sea level change.

The issue isn't the noise and fall at the 1883 mark, the issue is the shape of the two curves over the nearly 130 year time line, and the shape of the curve has everything to do with the question, “Is sea level rise accelerating?”

But, many of your points are valid, what I did is usually described as quick and dirty back of the napkin figuring and leaves a lot to be desired and is certainly not the fine tuned product of an academic opus. Which reminds me of an analogy.

Two guys buy the exact same type of car both EPA rated to get 30 mpg. One of the guys takes his car to a special mechanic for some fine tuning and now he claims to get 50 mpg. Doesn't add up. No one would believe it.

(-Snip-)

I’ve made that point several times now. I should give it a rest.

We have two separate measuring systems, tide gages and satellites. That they report different numbers ought not be a big surprise. In a machine shop there are many ways to measure dimensions; micrometers, coordinate measuring machines, optical comparators, gage pins, bore gages, calipers, snap gages, rulers, and a host of customized gages. They all give slightly different answers and each has their own uses. Trying to get them to all give the same answers is a fool’s errand. But that's what we seem to be doing by trying to match tide gages with the satellites.

And finally there’s an expression about picking the fly specks out of the pepper. Whether the rate of sea level bumps up 0.013 mm per year or not isn’t all that important. After all, if you run the numbers we’re only talking an extra 65 mm in 100 years.

Response:

[DB] Speculations of academic fraud snipped.

"I’ve made that point several times now. I should give it a rest."

Yes, you should. Any more violations of the Comments Policy will result in automatic deletion of your entire comments.

"After all, if you run the numbers we’re only talking an extra 65 mm in 100 years."

You make the classic error of presuming SLR will be linear when history gives us ample examples that SLR is highly nonlinear.

"But that's what we seem to be doing by trying to match tide gages with the satellites."

That's what real scientists, like Dr's Church and White, do. Amateurs struggling to replicate their work without a foundation in the science and a thorough understanding of the literature are the ones conducting the "fools errand".

Steve Case @33, that is an interesting analogy. However, it is fairly obvious in that analogy that Church and White are the EPA, while you are the back shed mechanic gaping spark plugs with a ball-pein hammer. I wonder why you do not draw the obvious conclusion.

Having said that:

1) The GIA may not effect the shape of the curve, but strong changes in the regional balance of your data will. What is more, failure to correct for barymetric pressure may also effect acceleration.

The different basins to not rise or sink synchronously. The reason for this is that major weather patterns such as ENSO or the NAO shift pressure patterns over large areas of ocean, with a consequent change in sea level as water is pushed from one part of the ocean to another. If your data set shows a regional bias, and this phenomenon is uncorrected, that will result in a significant distortion of the result, a distortion that change the acceleration pattern.

2) The issue is the noise, in that a large part of your failure to reproduce Church and White consists of the fact that you have not successfully excluded noise, and indeed have decreased the signal to noise ratio with your reconstruction technique.

3) It appears you have never worked in a workshop, for if you had you would recognize that if your means of measurement significantly disagree, you have a major problem. We may not expect the micrometer and the steel rule to give us exactly the same measurement, but if they are not identical plus or minus 0.5 mm, then either at least one is faulty, or your measurement technique is error prone.

4) See you are the one who chose to attack the science on this point, it is hypocritical of you to then accuse us of "picking the fly specks out of the pepper". You add to that hypocrisy an egregious error. The current rate of sea level rise is between 2 and 3.2 mm per year, leading to an expected sea level rise of 200 to 320 mm per century if nothing changes. Even as a simple projection you 65mm is an obvious error.

Such simple projections, are, however, significant underestimates both because they do not account for additional increases in temperature, nor for glacial melt water, which between them will push sea levels up by between 0.6 and 2 meters by the end of the century.

Not the most serious implication of global warming, but not negligible either.

Eric the Red @35, on the contrary, Jevrejeva et al, 2006 and Church and White 2006 (and 2011) both show that sea level rise as determined by gauges is within the error bars of that determined by satellite altimetry over concurrent periods. What is dissimilar is the current trend and those earlier in the twentieth century, which where lower.

You evidently want it to be true that there is a mismatch, but neither you nor Steve Case have given us any reason to believe it.

I thought that rising sea level is a negative aspect of "Climate Change" and that we in fact would like to not go there. So the choice of words, "Pothole on Road to", and hitting a "speed bump" are a bit mysterious. Terms like remission, respite, suspension, reprieve, let up, lull etc. weren't considered. Food for thought as to why that is.

Remission: cancer carries too much other baggage to be a good metaphor, even though mitigation can help reverse the trend.

Respite: that would be a good word, but its metaphorical value is not nearly as good as 'pothole'.

Suspension: nothing has been suspended. The forces working for sea level rise are still in place; they've simply been temporarily overbalanced by other forces.

Reprieve: a reprieve carries with it the sense of finality. Respite is better, but, again, both have little metaphorical sense.

Let up: indicates that the force at work has stopped working for a while. Not true.

Lull: ugh, not appropriate to a trend line.

The idea of a 'pothole' and a road serves the idea of a trend line well, and a road (and the implied driver) is a relevant image where the A in AGW is concerned (we are driving climate change at least partially through our mode of transport). A 'speed bump' further implies an accelerating rate. Potholes make me think of asphalt, too, and asphalt makes me think of oil.

Hello all. I recently stumbled upon a paper which states, in the abstract, that global mean sea level "rises with the rate of 3.2 ± 0.4 mm/yr during 1993–2003 and started decelerating since 2004 to a rate of 1.8 ± 0.9 mm/yr in 2012." This seems to indicate that sea level rise is decelerating globally (not just locally as was the case with Houston and Dean's paper). The paper can be viewed here. I would like to get some feedback on whether or not this does any damage to the apparently "consensus" view that sea level rise is accelerating.

jsmith - that paper has been doing the rounds on contrarian blogs, so you probably 'stumbled' across a contrarian blog.

I haven't looked at the research paper in detail, but the general slowing of sea level rise after 2004-2005 fits in with the sharp acceleration of heat uptake into the ocean during 2000-2005, and a slower rate of heat uptake thereafter. This 'slowdown' is perhaps the most striking feature of the Hiroshima widget.

The recent trend in sea level rise is consistent with ocean heat uptake, so we shouldn't be surprised that the recent trend in sea level rise has slowed somewhat too. A similar pattern seems to have occurred during the 20th century too - short-term accelerations and decelerations against a background of long-term acceleration in sea level rise.

There are a few other factors to consider too (decadal variations in continental storage of water mass, for example), but land-ice melt is accelerating and thermal expansion is not really going to be a factor throughout 21st Century - the disintegration of the vast ice sheets of Greenland and Antarctica will be.

You really need to look at multi-decadal time periods to determine trends, as in Church and White 2011 who found "1900 to 2009 is 1.7 ± 0.2 mm/year and since 1961 is 1.9 ± 0.4 mm/year" and "For 1993–2009 and after correcting for glacial isostatic adjustment, the estimated rate of rise is 3.2 ± 0.4 mm/year from the satellite data and 2.8 ± 0.8 mm/year from the in situ data". They also note that "There is considerable variability in the rate of rise during the twentieth century but there has been a statistically significant acceleration since 1880 and 1900 of 0.009 ± 0.003 mm/year2 and 0.009 ± 0.004 mm/year2, respectively." (Emphasis added)

Short time periods, such as a single decade, are only going to show noise, not trends. While I don't subscribe to that particular journal and have not read the entire article, I fear that the paper is not properly evaluating the statistical significance of their results. If they can clearly support their hypotheses it will be interesting - but as it stands I see little support for such claims.

Simple experiment:Fill a bucket to the top with water, then add a brick.What happens the water overflows the weight of the lost water equals the weight of the brick, it's called displacement.Add some thing to a body of water what happens?Throw a brick in the ocean, no noticeable difference.But throw billions of tons of bricks in and float thousands of ships and boats of all sizes on then we have Oceans rising,melting ice:add a large block of ice in your bucket then fill the bucket to the top, the ice floats above & below the water, as the ice melts will the water overflow? Remembering displacement,Check out below for some reasons for the rising of the oceans.Listed below is just a small amount of the reasons.

Apparently in WW1 a total of 375 U boats sank 6596 merchant ships, a total of 12,800,000 tons.

The Japanese lost 1,178 Merchant Ships sunk for a tonnage total of 5,053,491 tons. The Naval losses were 214 ships and submarines totaling 577,626 tons. A staggering five million, six hundred thirty one thousand, one hundred seventeen tons,(5,631,117 tons), 1,392 ships

It's estimated that 10,000 of these large containers are lost at sea each year, Average tonnage 18 tons180,000 tons per annum

According to an annual analysis from insurer Allianz, 94 ships on average(over 100 gross tonnes) each were completely lost in 2013. There are many reasons for a complete loss. “Foundering” (which means sinking or submerging) caused the vast majority of the big losses

Over 30,000 large Ships over 500 tons launched since 1975 not to mention the 100 of thousands sail boats small yatch's ferries etc

Now lets add the land Pushed into the ocean to build Airstrips, Islands & Erosion.Where doe's the water go, It just disappears, yeah right. “IT RISES”-NEWTONS LAW:For every action, there is an equal (in size) and opposite (in direction) reaction

Kerry Randell @42, taking your figures on total tonnage, and assuming the average container loss rate extends back to 1945, and that the average ship tonnage loss is 250 with the average loss also extending back to 1945, that yields a total 31,054,617 tonnes lost as a rough estimate. Given that the density of sea water is 1.025 Tonnes per meter cubed, that leads to an estimated displacement of 30,297,187 m^3 of displacement. Averaged over the ocean surface of 361, 132,000 km^2 of surface area, that leads to an estimated 0.000084 milimeter rise in sea level based on your assumptions, for the entirety of lost shipping in the 20th century.

However, that is likely a significant overestimate. The mass of water displaced only equals the mass of the object if the object is floating. If it sinks, the water displaced equals the volume of the immersed object, which is necessarilly less than the volume of water equal to the tonnage of the immersed object, for if it were not, the object would float rather than sink. Ergo, your initial assumption is completely wrong headed. The mass of water displaced by various vessels sunk at sea is far less than the displacement of the vessels.

Kerry... You're doing a classic "missing denominator" calculation. You've estimated out that the number of ships displacing sea water is a very large number. That's your numerator. Your denominator is the total tonnage of all the earth's oceans, and that would make the result an extremely small number.